/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

/*
 *    CostMatrix.java
 *    Copyright (C) 2006-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers;

import java.io.LineNumberReader;
import java.io.Reader;
import java.io.Serializable;
import java.io.StreamTokenizer;
import java.io.Writer;
import java.util.Random;
import java.util.StringTokenizer;

import weka.core.Instance;
import weka.core.Instances;
import weka.core.Utils;
import weka.core.expressionlanguage.common.IfElseMacro;
import weka.core.expressionlanguage.common.JavaMacro;
import weka.core.expressionlanguage.common.MacroDeclarationsCompositor;
import weka.core.expressionlanguage.common.MathFunctions;
import weka.core.expressionlanguage.common.Primitives.DoubleExpression;
import weka.core.expressionlanguage.core.Node;
import weka.core.expressionlanguage.parser.Parser;
import weka.core.expressionlanguage.weka.InstancesHelper;

/**
 * Class for storing and manipulating a misclassification cost matrix. The
 * element at position i,j in the matrix is the penalty for classifying an
 * instance of class j as class i. Cost values can be fixed or computed on a
 * per-instance basis (cost sensitive evaluation only) from the value of an
 * attribute or a mathematical expression involving attribute(s).<br>
 * <br>
 *
 * Values in an instance are accessed in an expression by prefixing their index
 * (starting at 1) with the character 'a'. E.g.<br>
 * <br>
 *
 * a1 &circ; 2 * a5 / log(a7 * 4.0) <br>
 * 
 * Supported opperators: +, -, *, /, ^, log, abs, cos, exp, sqrt, floor, ceil,
 * rint, tan, sin, (, ).
 * 
 *
 * 
 * 
 * @author Mark Hall
 * @author Richard Kirkby (rkirkby@cs.waikato.ac.nz)
 * @version $Revision$
 * @see weka.core.UnsupportedAttributeTypeException
 */
public class CostMatrix implements Serializable {

    /** for serialization */
    private static final long serialVersionUID = -1973792250544554965L;

    private int m_size;

    /** [rows][columns] */
    protected Object[][] m_matrix;

    /** The deafult file extension for cost matrix files */
    public static String FILE_EXTENSION = ".cost";

    /**
     * Creates a default cost matrix of a particular size. All diagonal values will
     * be 0 and all non-diagonal values 1.
     * 
     * @param numOfClasses the number of classes that the cost matrix holds.
     */
    public CostMatrix(int numOfClasses) {
        m_size = numOfClasses;
        initialize();
    }

    /**
     * Creates a cost matrix that is a copy of another.
     * 
     * @param toCopy the matrix to copy.
     */
    public CostMatrix(CostMatrix toCopy) {
        this(toCopy.size());

        for (int i = 0; i < m_size; i++) {
            for (int j = 0; j < m_size; j++) {
                setCell(i, j, toCopy.getCell(i, j));
            }
        }
    }

    /**
     * Initializes the matrix
     */
    public void initialize() {
        m_matrix = new Object[m_size][m_size];
        for (int i = 0; i < m_size; i++) {
            for (int j = 0; j < m_size; j++) {
                setCell(i, j, i == j ? new Double(0.0) : new Double(1.0));
            }
        }
    }

    /**
     * The number of rows (and columns)
     * 
     * @return the size of the matrix
     */
    public int size() {
        return m_size;
    }

    /**
     * Same as size
     * 
     * @return the number of columns
     */
    public int numColumns() {
        return size();
    }

    /**
     * Same as size
     * 
     * @return the number of rows
     */
    public int numRows() {
        return size();
    }

    private boolean replaceStrings(Instances dataset) throws Exception {
        boolean nonDouble = false;

        for (int i = 0; i < m_size; i++) {
            for (int j = 0; j < m_size; j++) {
                if (getCell(i, j) instanceof String) {
                    setCell(i, j, new InstanceExpression((String) getCell(i, j), dataset));
                    nonDouble = true;
                } else if (getCell(i, j) instanceof InstanceExpression) {
                    nonDouble = true;
                }
            }
        }

        return nonDouble;
    }

    /**
     * Applies the cost matrix to a set of instances. If a random number generator
     * is supplied the instances will be resampled, otherwise they will be
     * rewighted. Adapted from code once sitting in Instances.java
     * 
     * @param data   the instances to reweight.
     * @param random a random number generator for resampling, if null then
     *               instances are rewighted.
     * @return a new dataset reflecting the cost of misclassification.
     * @exception Exception if the data has no class or the matrix in inappropriate.
     */
    public Instances applyCostMatrix(Instances data, Random random) throws Exception {

        double sumOfWeightFactors = 0, sumOfMissClassWeights, sumOfWeights;
        double[] weightOfInstancesInClass, weightFactor, weightOfInstances;

        if (data.classIndex() < 0) {
            throw new Exception("Class index is not set!");
        }

        if (size() != data.numClasses()) {
            throw new Exception("Misclassification cost matrix has wrong format!");
        }

        // are there any non-fixed, per-instance costs defined in the matrix?
        if (replaceStrings(data)) {
            // could reweight in the two class case
            if (data.classAttribute().numValues() > 2) {
                throw new Exception("Can't resample/reweight instances using " + "non-fixed cost values when there are more " + "than two classes!");
            } else {
                // Store new weights
                weightOfInstances = new double[data.numInstances()];
                for (int i = 0; i < data.numInstances(); i++) {
                    Instance inst = data.instance(i);
                    int classValIndex = (int) inst.classValue();
                    double factor = 1.0;
                    Object element = (classValIndex == 0) ? getCell(classValIndex, 1) : getCell(classValIndex, 0);
                    if (element instanceof Double) {
                        factor = ((Double) element).doubleValue();
                    } else {
                        factor = ((InstanceExpression) element).evaluate(inst);
                    }
                    weightOfInstances[i] = inst.weight() * factor;
                    /*
                     * System.err.println("Multiplying " +
                     * inst.classAttribute().value((int)inst.classValue()) +" by factor " + factor);
                     */
                }

                // Change instances weight or do resampling
                if (random != null) {
                    return data.resampleWithWeights(random, weightOfInstances);
                } else {
                    Instances instances = new Instances(data);
                    for (int i = 0; i < data.numInstances(); i++) {
                        instances.instance(i).setWeight(weightOfInstances[i]);
                    }
                    return instances;
                }
            }
        }

        weightFactor = new double[data.numClasses()];
        weightOfInstancesInClass = new double[data.numClasses()];
        for (int j = 0; j < data.numInstances(); j++) {
            weightOfInstancesInClass[(int) data.instance(j).classValue()] += data.instance(j).weight();
        }
        sumOfWeights = Utils.sum(weightOfInstancesInClass);

        // normalize the matrix if not already
        for (int i = 0; i < m_size; i++) {
            if (!Utils.eq(((Double) getCell(i, i)).doubleValue(), 0)) {
                CostMatrix normMatrix = new CostMatrix(this);
                normMatrix.normalize();
                return normMatrix.applyCostMatrix(data, random);
            }
        }

        for (int i = 0; i < data.numClasses(); i++) {
            // Using Kai Ming Ting's formula for deriving weights for
            // the classes and Breiman's heuristic for multiclass
            // problems.

            sumOfMissClassWeights = 0;
            for (int j = 0; j < data.numClasses(); j++) {
                if (Utils.sm(((Double) getCell(i, j)).doubleValue(), 0)) {
                    throw new Exception("Neg. weights in misclassification " + "cost matrix!");
                }
                sumOfMissClassWeights += ((Double) getCell(i, j)).doubleValue();
            }
            weightFactor[i] = sumOfMissClassWeights * sumOfWeights;
            sumOfWeightFactors += sumOfMissClassWeights * weightOfInstancesInClass[i];
        }
        for (int i = 0; i < data.numClasses(); i++) {
            weightFactor[i] /= sumOfWeightFactors;
        }

        // Store new weights
        weightOfInstances = new double[data.numInstances()];
        for (int i = 0; i < data.numInstances(); i++) {
            weightOfInstances[i] = data.instance(i).weight() * weightFactor[(int) data.instance(i).classValue()];
        }

        // Change instances weight or do resampling
        if (random != null) {
            return data.resampleWithWeights(random, weightOfInstances);
        } else {
            Instances instances = new Instances(data);
            for (int i = 0; i < data.numInstances(); i++) {
                instances.instance(i).setWeight(weightOfInstances[i]);
            }
            return instances;
        }
    }

    /**
     * Calculates the expected misclassification cost for each possible class value,
     * given class probability estimates.
     * 
     * @param classProbs the class probability estimates.
     * @return the expected costs.
     * @exception Exception if the wrong number of class probabilities is supplied.
     */
    public double[] expectedCosts(double[] classProbs) throws Exception {

        if (classProbs.length != m_size) {
            throw new Exception("Length of probability estimates don't " + "match cost matrix");
        }

        double[] costs = new double[m_size];

        for (int x = 0; x < m_size; x++) {
            for (int y = 0; y < m_size; y++) {
                Object element = getCell(y, x);
                if (!(element instanceof Double)) {
                    throw new Exception("Can't use non-fixed costs in " + "computing expected costs.");
                }
                costs[x] += classProbs[y] * ((Double) element).doubleValue();
            }
        }

        return costs;
    }

    /**
     * Calculates the expected misclassification cost for each possible class value,
     * given class probability estimates.
     * 
     * @param classProbs the class probability estimates.
     * @param inst       the current instance for which the class probabilites
     *                   apply. Is used for computing any non-fixed cost values.
     * @return the expected costs.
     * @exception Exception if something goes wrong
     */
    public double[] expectedCosts(double[] classProbs, Instance inst) throws Exception {

        if (classProbs.length != m_size) {
            throw new Exception("Length of probability estimates don't " + "match cost matrix");
        }

        if (!replaceStrings(inst.dataset())) {
            return expectedCosts(classProbs);
        }

        double[] costs = new double[m_size];

        for (int x = 0; x < m_size; x++) {
            for (int y = 0; y < m_size; y++) {
                Object element = getCell(y, x);
                double costVal;
                if (!(element instanceof Double)) {
                    costVal = ((InstanceExpression) element).evaluate(inst);
                } else {
                    costVal = ((Double) element).doubleValue();
                }
                costs[x] += classProbs[y] * costVal;
            }
        }

        return costs;
    }

    /**
     * Gets the maximum cost for a particular class value.
     * 
     * @param classVal the class value.
     * @return the maximum cost.
     * @exception Exception if cost matrix contains non-fixed costs
     */
    public double getMaxCost(int classVal) throws Exception {

        double maxCost = Double.NEGATIVE_INFINITY;

        for (int i = 0; i < m_size; i++) {
            Object element = getCell(classVal, i);
            if (!(element instanceof Double)) {
                throw new Exception("Can't use non-fixed costs when " + "getting max cost.");
            }
            double cost = ((Double) element).doubleValue();
            if (cost > maxCost)
                maxCost = cost;
        }

        return maxCost;
    }

    /**
     * Gets the maximum cost for a particular class value.
     * 
     * @param classVal the class value.
     * @return the maximum cost.
     * @exception Exception if cost matrix contains non-fixed costs
     */
    public double getMaxCost(int classVal, Instance inst) throws Exception {

        if (!replaceStrings(inst.dataset())) {
            return getMaxCost(classVal);
        }

        double maxCost = Double.NEGATIVE_INFINITY;
        double cost;
        for (int i = 0; i < m_size; i++) {
            Object element = getCell(classVal, i);
            if (!(element instanceof Double)) {
                cost = ((InstanceExpression) element).evaluate(inst);
            } else {
                cost = ((Double) element).doubleValue();
            }
            if (cost > maxCost)
                maxCost = cost;
        }

        return maxCost;
    }

    /**
     * Normalizes the matrix so that the diagonal contains zeros.
     * 
     */
    public void normalize() {

        for (int y = 0; y < m_size; y++) {
            double diag = ((Double) getCell(y, y)).doubleValue();
            for (int x = 0; x < m_size; x++) {
                setCell(x, y, new Double(((Double) getCell(x, y)).doubleValue() - diag));
            }
        }
    }

    /**
     * Loads a cost matrix in the old format from a reader. Adapted from code once
     * sitting in Instances.java
     * 
     * @param reader the reader to get the values from.
     * @exception Exception if the matrix cannot be read correctly.
     */
    public void readOldFormat(Reader reader) throws Exception {

        StreamTokenizer tokenizer;
        int currentToken;
        double firstIndex, secondIndex, weight;

        tokenizer = new StreamTokenizer(reader);

        initialize();

        tokenizer.commentChar('%');
        tokenizer.eolIsSignificant(true);
        while (StreamTokenizer.TT_EOF != (currentToken = tokenizer.nextToken())) {

            // Skip empty lines
            if (currentToken == StreamTokenizer.TT_EOL) {
                continue;
            }

            // Get index of first class.
            if (currentToken != StreamTokenizer.TT_NUMBER) {
                throw new Exception("Only numbers and comments allowed " + "in cost file!");
            }
            firstIndex = tokenizer.nval;
            if (!Utils.eq((int) firstIndex, firstIndex)) {
                throw new Exception("First number in line has to be " + "index of a class!");
            }
            if ((int) firstIndex >= size()) {
                throw new Exception("Class index out of range!");
            }

            // Get index of second class.
            if (StreamTokenizer.TT_EOF == (currentToken = tokenizer.nextToken())) {
                throw new Exception("Premature end of file!");
            }
            if (currentToken == StreamTokenizer.TT_EOL) {
                throw new Exception("Premature end of line!");
            }
            if (currentToken != StreamTokenizer.TT_NUMBER) {
                throw new Exception("Only numbers and comments allowed " + "in cost file!");
            }
            secondIndex = tokenizer.nval;
            if (!Utils.eq((int) secondIndex, secondIndex)) {
                throw new Exception("Second number in line has to be " + "index of a class!");
            }
            if ((int) secondIndex >= size()) {
                throw new Exception("Class index out of range!");
            }
            if ((int) secondIndex == (int) firstIndex) {
                throw new Exception("Diagonal of cost matrix non-zero!");
            }

            // Get cost factor.
            if (StreamTokenizer.TT_EOF == (currentToken = tokenizer.nextToken())) {
                throw new Exception("Premature end of file!");
            }
            if (currentToken == StreamTokenizer.TT_EOL) {
                throw new Exception("Premature end of line!");
            }
            if (currentToken != StreamTokenizer.TT_NUMBER) {
                throw new Exception("Only numbers and comments allowed " + "in cost file!");
            }
            weight = tokenizer.nval;
            if (!Utils.gr(weight, 0)) {
                throw new Exception("Only positive weights allowed!");
            }
            setCell((int) firstIndex, (int) secondIndex, new Double(weight));
        }
    }

    /**
     * Reads a matrix from a reader. The first line in the file should contain the
     * number of rows and columns. Subsequent lines contain elements of the matrix.
     * (FracPete: taken from old weka.core.Matrix class)
     * 
     * @param reader the reader containing the matrix
     * @throws Exception if an error occurs
     * @see #write(Writer)
     */
    public CostMatrix(Reader reader) throws Exception {
        LineNumberReader lnr = new LineNumberReader(reader);
        String line;
        int currentRow = -1;

        while ((line = lnr.readLine()) != null) {

            // Comments
            if (line.startsWith("%")) {
                continue;
            }

            StringTokenizer st = new StringTokenizer(line);
            // Ignore blank lines
            if (!st.hasMoreTokens()) {
                continue;
            }

            if (currentRow < 0) {
                int rows = Integer.parseInt(st.nextToken());
                if (!st.hasMoreTokens()) {
                    throw new Exception("Line " + lnr.getLineNumber() + ": expected number of columns");
                }

                int cols = Integer.parseInt(st.nextToken());
                if (rows != cols) {
                    throw new Exception("Trying to create a non-square cost " + "matrix");
                }
                // m_matrix = new Object[rows][cols];
                m_size = rows;
                initialize();
                currentRow++;
                continue;

            } else {
                if (currentRow == m_size) {
                    throw new Exception("Line " + lnr.getLineNumber() + ": too many rows provided");
                }

                for (int i = 0; i < m_size; i++) {
                    if (!st.hasMoreTokens()) {
                        throw new Exception("Line " + lnr.getLineNumber() + ": too few matrix elements provided");
                    }

                    String nextTok = st.nextToken();
                    // try to parse as a double first
                    Double val = null;
                    try {
                        val = new Double(nextTok);
                    } catch (Exception ex) {
                        val = null;
                    }
                    if (val == null) {
                        setCell(currentRow, i, nextTok);
                    } else {
                        setCell(currentRow, i, val);
                    }
                }
                currentRow++;
            }
        }

        if (currentRow == -1) {
            throw new Exception("Line " + lnr.getLineNumber() + ": expected number of rows");
        } else if (currentRow != m_size) {
            throw new Exception("Line " + lnr.getLineNumber() + ": too few rows provided");
        }
    }

    /**
     * Writes out a matrix. The format can be read via the CostMatrix(Reader)
     * constructor. (FracPete: taken from old weka.core.Matrix class)
     * 
     * @param w the output Writer
     * @throws Exception if an error occurs
     */
    public void write(Writer w) throws Exception {
        w.write("% Rows\tColumns\n");
        w.write("" + m_size + "\t" + m_size + "\n");
        w.write("% Matrix elements\n");
        for (int i = 0; i < m_size; i++) {
            for (int j = 0; j < m_size; j++) {
                w.write("" + getCell(i, j) + "\t");
            }
            w.write("\n");
        }
        w.flush();
    }

    /**
     * converts the Matrix into a single line Matlab string: matrix is enclosed by
     * parentheses, rows are separated by semicolon and single cells by blanks,
     * e.g., [1 2; 3 4].
     * 
     * @return the matrix in Matlab single line format
     */
    public String toMatlab() {
        StringBuffer result;
        int i;
        int n;

        result = new StringBuffer();

        result.append("[");

        for (i = 0; i < m_size; i++) {
            if (i > 0) {
                result.append("; ");
            }

            for (n = 0; n < m_size; n++) {
                if (n > 0) {
                    result.append(" ");
                }
                result.append(getCell(i, n));
            }
        }

        result.append("]");

        return result.toString();
    }

    /**
     * creates a matrix from the given Matlab string.
     * 
     * @param matlab the matrix in matlab format
     * @return the matrix represented by the given string
     * @see #toMatlab()
     */
    public static CostMatrix parseMatlab(String matlab) throws Exception {
        StringTokenizer tokRow;
        StringTokenizer tokCol;
        int rows;
        int cols;
        CostMatrix result;
        String cells;

        // get content
        cells = matlab.substring(matlab.indexOf("[") + 1, matlab.indexOf("]")).trim();

        // determine dimenions
        tokRow = new StringTokenizer(cells, ";");
        rows = tokRow.countTokens();
        tokCol = new StringTokenizer(tokRow.nextToken(), " ");
        cols = tokCol.countTokens();

        // fill matrix
        result = new CostMatrix(rows);
        tokRow = new StringTokenizer(cells, ";");
        rows = 0;
        while (tokRow.hasMoreTokens()) {
            tokCol = new StringTokenizer(tokRow.nextToken(), " ");
            cols = 0;
            while (tokCol.hasMoreTokens()) {
                // is it a number
                String current = tokCol.nextToken();
                try {
                    double val = Double.parseDouble(current);
                    result.setCell(rows, cols, new Double(val));
                } catch (NumberFormatException e) {
                    // must be an expression
                    result.setCell(rows, cols, current);
                }
                cols++;
            }
            rows++;
        }

        return result;
    }

    /**
     * Set the value of a particular cell in the matrix
     * 
     * @param rowIndex    the row
     * @param columnIndex the column
     * @param value       the value to set
     */
    public final void setCell(int rowIndex, int columnIndex, Object value) {
        m_matrix[rowIndex][columnIndex] = value;
    }

    /**
     * Return the contents of a particular cell. Note: this method returns the
     * Object stored at a particular cell.
     * 
     * @param rowIndex    the row
     * @param columnIndex the column
     * @return the value at the cell
     */
    public final Object getCell(int rowIndex, int columnIndex) {
        return m_matrix[rowIndex][columnIndex];
    }

    /**
     * Return the value of a cell as a double (for legacy code)
     * 
     * @param rowIndex    the row
     * @param columnIndex the column
     * @return the value at a particular cell as a double
     * @exception Exception if the value is not a double
     */
    public final double getElement(int rowIndex, int columnIndex) throws Exception {
        if (!(m_matrix[rowIndex][columnIndex] instanceof Double)) {
            throw new Exception("Cost matrix contains non-fixed costs!");
        }
        return ((Double) m_matrix[rowIndex][columnIndex]).doubleValue();
    }

    /**
     * Return the value of a cell as a double. Computes the value for non-fixed
     * costs using the supplied Instance
     * 
     * @param rowIndex    the row
     * @param columnIndex the column
     * @return the value from a particular cell
     * @exception Exception if something goes wrong
     */
    public final double getElement(int rowIndex, int columnIndex, Instance inst) throws Exception {

        if (m_matrix[rowIndex][columnIndex] instanceof Double) {
            return ((Double) m_matrix[rowIndex][columnIndex]).doubleValue();
        } else if (m_matrix[rowIndex][columnIndex] instanceof String) {
            replaceStrings(inst.dataset());
        }

        return ((InstanceExpression) m_matrix[rowIndex][columnIndex]).evaluate(inst);
    }

    /**
     * Set the value of a cell as a double
     * 
     * @param rowIndex    the row
     * @param columnIndex the column
     * @param value       the value (double) to set
     */
    public final void setElement(int rowIndex, int columnIndex, double value) {
        m_matrix[rowIndex][columnIndex] = new Double(value);
    }

    /**
     * Converts a matrix to a string. (FracPete: taken from old weka.core.Matrix
     * class)
     * 
     * @return the converted string
     */
    @Override
    public String toString() {
        // Determine the width required for the maximum element,
        // and check for fractional display requirement.
        double maxval = 0;
        boolean fractional = false;
        Object element = null;
        int widthNumber = 0;
        int widthExpression = 0;
        for (int i = 0; i < size(); i++) {
            for (int j = 0; j < size(); j++) {
                element = getCell(i, j);
                if (element instanceof Double) {
                    double current = ((Double) element).doubleValue();

                    if (current < 0)
                        current *= -11;
                    if (current > maxval)
                        maxval = current;
                    double fract = Math.abs(current - Math.rint(current));
                    if (!fractional && ((Math.log(fract) / Math.log(10)) >= -2)) {
                        fractional = true;
                    }
                } else {
                    if (element.toString().length() > widthExpression) {
                        widthExpression = element.toString().length();
                    }
                }
            }
        }
        if (maxval > 0) {
            widthNumber = (int) (Math.log(maxval) / Math.log(10) + (fractional ? 4 : 1));
        }

        int width = (widthNumber > widthExpression) ? widthNumber : widthExpression;

        StringBuffer text = new StringBuffer();
        for (int i = 0; i < size(); i++) {
            for (int j = 0; j < size(); j++) {
                element = getCell(i, j);
                if (element instanceof Double) {
                    text.append(" ").append(Utils.doubleToString(((Double) element).doubleValue(), width, (fractional ? 2 : 0)));
                } else {
                    int diff = width - element.toString().length();
                    if (diff > 0) {
                        int left = diff % 2;
                        left += diff / 2;
                        String temp = Utils.padLeft(element.toString(), element.toString().length() + left);
                        temp = Utils.padRight(temp, width);
                        text.append(" ").append(temp);
                    } else {
                        text.append(" ").append(element.toString());
                    }
                }
            }
            text.append("\n");
        }

        return text.toString();
    }


    private static class InstanceExpression {
        private final DoubleExpression m_compiledExpression;
        private final String m_expression;
        private final InstancesHelper m_instancesHelper;

        public InstanceExpression(String expression, Instances dataset) throws Exception {
            this.m_expression = expression;
            m_instancesHelper = new InstancesHelper(dataset);

            Node node = Parser.parse(
                    // expression
                    expression,
                    // variables
                    m_instancesHelper,
                    // marcos
                    new MacroDeclarationsCompositor(m_instancesHelper, new MathFunctions(), new IfElseMacro(), new JavaMacro()));

            if (!(node instanceof DoubleExpression))
                throw new Exception("Expression must be of double type!");

            m_compiledExpression = (DoubleExpression) node;
        }

        public double evaluate(Instance inst) {
            m_instancesHelper.setInstance(inst);
            return m_compiledExpression.evaluate();
        }

        @Override
        public String toString() {
            return m_expression;
        }
    }
}
